Extending Deep Nets to New, Unexpected Situations
Extending Deep Nets to New, Unexpected Situations
Deep neural networks could very well memorize their training data, but instead they find generalizable rules.We will discuss various ideas for why this happens, and how we can build deep learning systems that generalize even better to new and unexpected scenarios
Speakers
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Class of 1948 Career Development Professor, Department of Electrical Engineering and Computer ScienceComputer Science and Artificial Intelligence Laboratory- Computer Vision
- AI Explainability
- Machine Learning
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Steven G (1968) and Renee Finn CD Assistant Professor, Department of Electrical Engineering and Computer ScienceComputer Science and Artificial Intelligence LaboratoryLaboratory for Information and Decision Systems- Computer Vision
- Machine Learning
- AI Robotics
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Schedule
Schedule
Date: Thursday, February 11, 2021
Time: 7pm - 8pm EST
Where: Zoom Webinar
7:00 PM - 7:05 PM
Introduction
Aude Oliva
7:05 PM - 7:25 PM
Why do Deep Nets Generalize?
Phillip Isola
7:25 PM - 7:40 PM
"Unwanted" Generalization
Pulkit Agrawal
7:40 PM - 8:00 PM
Roundtable Discussion and Q&A
Phillip Isola, Pulkit Agrawal, Alyosha Efros and Aude Oliva
Register
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